Target apply and provisioning
Capture speed matters only when the destination can keep up.
Omni Loader selects target-specific apply strategies, creates compatible schemas where supported, and isolates unsafe records.
SourcesConcurrent
Oracle
SQL Server
PostgreSQL
MySQL
MariaDB
Sybase ASE
Oracle
SQL Server
PostgreSQL
MySQL
MariaDB
Sybase ASE Omni Loader Burst Load + continuous CDC
Live
Parallel readN-way
D1
D2
D3
D4
spool
Parallel applyN-way
A1
A2
A3
A4
Committed order preservedIndependent sink cursors
SinksIndependent
PostgreSQL
MySQL
SQL Server
Azure SQL
Oracle
Sybase ASE
Google Cloud Spanner
Fabric Open Mirroring
PostgreSQL
MySQL
SQL Server
Azure SQL
Oracle
Sybase ASE
Google Cloud SpannerK Apache Kafka
P Google Pub/Sub
Fabric Open MirroringPreflight
Choose safely
Analyze keys and target behavior first.
Parallel
Use stable keys
Hash keyed work while preserving barriers.
Convergent
Replay safely
Use staged operations and durable ledgers.
Destination-native execution
Use the database as a database.
PostgreSQL, SQL Server, and Oracle can use staged convergent bulk apply. Other paths use grouped statements, upserts, batching, and connection reuse.
✓ Insert, update, delete, truncate, and key-change barriers
✓ Stable-key parallel apply
✓ Group commit and batch coalescing
✓ Target-specific type mapping
Provision deliberately
Create compatible targets without hiding DDL.
Schema check and create are explicit. Omni Loader provisions PostgreSQL, SQL Server, Azure SQL, MySQL, and Oracle targets.
✓ Source description and target comparison
✓ Key-safe type sizing
✓ Fail, skip, and dead-letter policy
✓ Binary split to isolate a bad record
Keep exploring
See the connected parts of the platform.
Size the pipeline at the destination boundary.
Bring representative keys, rows, indexes, and DML. We will select provisioning and apply profiles.